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Fields, Deborah; Lui, Debora; Kafai, Yasmin; Jayathirtha, Gayithri; Walker, Justice; Shaw, Mia – Computer Science Education, 2021
Background and Context: While assessment of computational thinking concepts, practices, and perspectives is at the forefront of K-12 CS education, supporting student "communication about computation" has received relatively little attention. Objective: To examine the usability of process-based portfolios for capturing students'…
Descriptors: Computer Science Education, Computation, Thinking Skills, Student Projects
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Huo, Rongrong – European Journal of Science and Mathematics Education, 2023
In our investigation of university students' knowledge about real numbers in relation to computer algebra systems (CAS) and how it could be developed in view of their future activity as teachers, we used a computer algorithm as a case to explore the relationship between CAS and the knowledge of real numbers as decimal representations. Our work was…
Descriptors: Numbers, Computer Science Education, Knowledge Level, Algorithms
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Robin Jocius; Jennifer Albert; Deepti Joshi; Melanie Blanton; Ian O'Byrne – Journal of Technology and Teacher Education, 2023
There is growing attention to the potential for developing professional learning experiences for content area teachers to infuse computational thinking (CT), which refers to the set of problem-solving practices related to the computer science discipline, into their classrooms. Although research has begun to document professional learning models…
Descriptors: Decision Making, Teaching Experience, Research Projects, Teacher Researchers
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Papamitsiou, Zacharoula; Economides, Anastasios A. – IEEE Transactions on Learning Technologies, 2020
Recommending educational resources to groups of students is a common task in collaborative learning contexts. However, differences in within-group motivational factors might lead to conflicts in students' intention to use the resources. Previous methods fail to achieve high goodness of recommendation for the majority of students in heterogeneous…
Descriptors: Student Motivation, Cooperative Learning, Game Theory, Educational Resources
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Stange, Melissa – Inquiry, 2020
This paper will discuss why technical skills alone will not be enough for students to have successful careers in the digital age. Much of their success will hinge on critical soft skills, such as adaptability, inner strength, holistic thinking, and a collaborative spirit. Examples will be provided for inclusion with a computer science program, but…
Descriptors: Technological Literacy, 21st Century Skills, Computer Science Education, Adjustment (to Environment)
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Morrison, Briana B.; Margulieux, Lauren E.; Decker, Adrienne – Computer Science Education, 2020
Background and Context: Subgoal labeled worked examples have been extensively researched, but the research has been reported piecemeal. This paper aggregates data from three studies, including data previously unreported, to holistically examine the effect of subgoal labeled worked examples across three student populations and across different…
Descriptors: Computer Science Education, Instructional Materials, Instructional Effectiveness, Problem Solving
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Hosseini, Roya; Akhuseyinoglu, Kamil; Brusilovsky, Peter; Malmi, Lauri; Pollari-Malmi, Kerttu; Schunn, Christian; Sirkiä, Teemu – International Journal of Artificial Intelligence in Education, 2020
This research is focused on how to support students' acquisition of program construction skills through worked examples. Although examples have been consistently proven to be valuable for student's learning, the learning technology for computer science education lacks program construction examples with interactive elements that could engage…
Descriptors: Programming, Computer Science Education, Problem Solving, Learner Engagement
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Statter, David; Armoni, Michal – ACM Transactions on Computing Education, 2020
Abstraction is one of the most fundamental ideas in computer science (CS), and as such, according to Bruner, it should be taught spirally, starting as early as possible and revisited at every level of education. However, teaching CS abstraction to novices is a very challenging task, and CS educational research has often demonstrated students'…
Descriptors: Middle School Students, Grade 7, Computer Science Education, Abstract Reasoning
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Rich, Kathryn M.; Spaepen, Elizabet; Strickland, Carla; Moran, Cheryl – Interactive Learning Environments, 2020
A key debate in computer science education is whether and how computational thinking (CT) is used within disciplines other than computer science. Broad definitions provide many avenues for developing integrated instruction, as practices within existing activities can simply be reframed in terms of CT. But such general use of the term CT may…
Descriptors: Computer Science Education, Mathematics Education, Mathematics Skills, Elementary School Students
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Kiliç, Servet; Gökoglu, Seyfullah; Öztürk, Mücahit – Journal of Educational Computing Research, 2021
In this research, a scale was developed to determine the programming-oriented computational thinking skills of university students. The participants were 360 students studying in various departments at different universities in Turkey for computer programming. The scale consists of 33 items under conceptual knowledge, algorithmic thinking, and…
Descriptors: Test Validity, Test Reliability, Test Construction, Programming
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Revshenova, Makhabbat; Bidaibekov, Esen; Kornilov, Victor; Kamalova, Guldina; Shekerbekova, Shirinkyz; Gulzhan, Seitbekova; Sabrayev, Kanat – Cypriot Journal of Educational Sciences, 2021
Bachelors and graduate students are offered in the course of teaching computational informatics, the ability to solve nonstandard mathematical problems, which, as a rule, are not included in the content of teaching computational informatics. The article aimed to analyze the application effectiveness of non-standard mathematical problems in the…
Descriptors: Professional Development, Competency Based Education, Preservice Teacher Education, Preservice Teachers
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Csizmadia, Andrew; Standl, Bernhard; Waite, Jane – Informatics in Education, 2019
In computer science education at school, computational thinking has been an emerging topic over the last decade. Even though, computational thinking is interpreted and integrated in classrooms in different ways, an identification process about what computational thinking is about has been in progress among computer science school-teachers and…
Descriptors: Constructivism (Learning), Computation, Thinking Skills, Class Activities
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Kwon, Kyungbin; Cheon, Jongpil – International Journal of Computer Science Education in Schools, 2019
Although teachers need to assess computational thinking (CT) for computer science education in K-12, it is not easy for them to evaluate students' programs based on the perspective. The purpose of this study was to investigate students' CT skills reflected in their Scratch programs. The context of the study was a middle school coding club where…
Descriptors: Computer Science Education, Computation, Thinking Skills, Coding
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Prates, Jorge Marques; Melo, Silvana Morita; Valle, Pedro Henrique Dias; Garcia, Rogério Eduardo; Maldonado, José Carlos – Informatics in Education, 2023
Nowadays, SPOCs (Small Private Online Courses) have been used as complementary methods to support classroom teaching. SPOCs are courses that apply the usage of MOOCs (Massive Open Online Courses), combining classroom with online education, making them an exciting alternative for contexts such as emergency remote teaching. Although SPOCs have been…
Descriptors: Computer Software, Computer Science Education, COVID-19, Pandemics
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Kleinman, Erica; Shergadwala, Murtuza N.; Teng, Zhaoqing; Villareale, Jennifer; Bryant, Andy; Zhu, Jichen; Seif El-Nasr, Magy – Journal of Learning Analytics, 2022
Educational technology is shifting toward facilitating personalized learning. Such personalization, however, requires a detailed understanding of students' problem-solving processes. Sequence analysis (SA) is a promising approach to gaining granular insights into student problem solving; however, existing techniques are difficult to interpret…
Descriptors: Problem Solving, Learning Analytics, Decision Making, Educational Technology
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